International Journal of Digital Earth

Humans in the City: Artificial Intelligence Research and Urban Environments

As urban areas are evolving into increasingly complex ecosystems, the integration of artificial intelligence can offer unique insights into urban structures and developments, as well as the behavior, decision-making processes, and interactions of people within cities. This collection aims to explore the forefront of AI-powered models and technologies for the investigation of human behavior and urban environments.

We seek to investigate how AI can be utilized to understand and model both environmental aspects and human-related dynamics in urban settings, ultimately supporting and enhancing the experience of city living through technological innovations and environmental changes. By leveraging AI, we can gain deeper insights into various urban dynamics leading to smarter, more sustainable cities. Moreover, AI has the potential to revolutionize urban planning and development by providing data-driven solutions. Through advanced algorithms and machine learning techniques, we can predict and mitigate the impact of urbanization on both the environment and the inhabitants.

This collection invites researchers, practitioners, and policymakers to explore the transformative potential of AI in urban environments. By harnessing the power of AI, we can create cities that are not only more intelligent and efficient but also more liveable and equitable for all residents. Join us in this endeavor to push the boundaries of what is possible in urban innovation and to shape the future of city living for generations to come.

Key topics and areas of interest include, but are not limited to three broad areas: human behavior and interaction analysis, urban systems and mobility, and related data and methods. The following list provides examples related to each of these broad areas, at different levels of granularity:

1. Human Activity Recognition: HAR in the context of human interactions within cities.
2. Navigation in the City: AI-based modeling and prediction of pedestrians’/ bikers’/ drivers’ behavior.
3. Study and Prediction of Urban Changes: Using AI to predict changes like urban Land Use Land Cover, urban growth, etc.
4. Urban Analytics: Employing AI to model the complexity of urban structures, model urban mobility, optimize urban traffic, and enhance transportation systems.
5. Urban Planning and Smart Cities: Application of AI in urban analytics, planning, and the development of smart city solutions.
6. Utilizing AI to Address Sustainability Challenges in Urban Environments, e.g., AI based interventions to alter human behavior towards sustainable mobility choices
7. Data Sources: AI as an assistance tool for data collection and processing from various sources, e.g., Volunteered Geographic Information (VGI)/ crowd-sourcing, sensory data, etc.
8. Geospatial Data Quality Assessment and its Impact on AI Models (e.g., missing data and biases)